Raw materials such as rolls of nonwoven, film, and paper materials are commonly used in the production of many articles. For example, disposable diapers may employ rolls of breathable cover materials, highly porous inner linings, hook and loop materials for fastening systems, elastomeric components, tissue webs, and other webs for their manufacture. For any material, the properties and/or form of the material may vary from batch to batch, or even within a single batch. For example, the roll size, mass, and basis weight may vary. In addition, there may be defects present in different areas of different rolls.
In some manufacturing systems, standard settings used in the processes that employ the material typically are not adapted to prevent difficulties that might arise from variability in material properties. In intelligent manufacturing systems, event-based information obtained during the production of goods can be used in a feed-forward process control system to adapt operating conditions to reduce waste and delay (see, for example, US Patent Publication No. U.S. 20030155415-A1, “Communication between Machines and Feed-Forward Control in Event-Based Product Manufacturing,” published Aug. 21, 2003 by Markham et al.). However, extensions of such concepts for improved manufacturing and material handling are desired.
For example, material handling equipment or other lifting devices such as forklifts or hoists move materials to needed locations in a manufacturing facility. Some of the lifting devices that move the materials have a variety of adjustments that an operator presently makes manually. Several problems are encountered in handling the materials due in part to the wide variety of weights that may be encountered (e.g., depending on the grade of material) and the need to make such changes manually. For example, the material weight may be greater than anticipated, resulting in damage to the material (e.g., dropping) as the lifting device operator makes manual adjustments to handle the particular material.
Accordingly, there is a need for systems and methods that automatically and accurately determine and adjust parameters of the lifting device to improve raw material handling.